Archive for the ‘Big Data’ Category

Many fans would argue that the Netflix original series “House of Cards” is the perfect television show – it has a fabulous production team, compelling leading actor, and stories of drama and betrayal that keep viewers on the edge of their seats. Turns out, this was no happy accident – this and all other Netflix series have been engineered with the use of Big Data and cloud computing to create the ideal television experience. So how does it all work?

“Film and television producers have always used data, holding previews for focus groups and logging the results, but as a technology company that distributes and now produces content, Netflix has mind-boggling access to consumer sentiment in real time,” Carr explained.

What is new, however, is how specific this information can get thanks to data willingly provided by the millions of users who make up the cloud hosting giant Netflix’s clients. Boiled down, here is how the American version of “House of Cards” came to be – analysts recognized that David Fincher, the show’s director, was a popular director on the site and unlike most videos, viewers tended to watch his work from beginning to end. When examining which actors appeared frequently in movies or television that users would stick with for the duration, Kevin Spacey fared well as did the original British version of “House of Cards.” Although there were other successful artists on the table for the project, Netflix narrowed its scope down to these three major contributors to inform its programming decision, to great acclaim.

When it began to produce its own shows as a part of the video platform, Netflix had plenty of user-provided information to draw upon. With more than 30 million video plays logged each day in its cloud infrastructure, the company employs analysts to make note of emerging trends, both to inform future products and help identify “You May Also Enjoy” options for fans of a certain genre. The company also examines which devices are most popular for streaming and which don’t encourage further watching to decide which they will continue to develop.

Part of what makes Big Data such a unique technological development is its adaptability to a number of different industries, transitioning between fashion analytics and cancer statistics without missing a beat. Although some companies are making use of Big Data to compile more accurate marketing statistics, others are using the cloud computing technology to predict what major weather events are on the horizon in any given area.

How Big Data can tell you when there’s a storm afoot.

Forbes contributor Lisa Wirthman wrote a recent article on how Big Data will assume an important role in this year’s impending hurricane season. In it, she explained how Big Data could be used to help those preparing for such storm thanks to analytics that could save their homes this season.

How does Big Data help predict the weather?
Ever since humans began studying thousands of weather patterns in an effort to better predict what was coming their way, analysis has been at the heart of efficiency when it comes to weather predictions. Technology has done a great deal to help forecasters predict anything from the smallest rainstorm to a monumental tornado, with varying degrees of accuracy.

The growth of Big Data meant that even more data could be collected, although the industry continued to focus mainly on aerial technology to predict developments of interest to readers and viewers. In recent years, as Wirthman explained, “hurricane hunters” have been able to get closer than ever to predicting the specifics of a particular storm.

“Although manned Hurricane Hunters can fly straight into the core of a storm, they typically don’t fly below 5,000 feet,” the source explained. “The Hunters can drop small cylinders into this low-level danger zone to gather data about temperature, humidity and pressure, but they only stay in the air for a few minutes before hitting the sea below.”

The need for database speed is always a given. Recently, application response time has been shown to not only provide customers with a better experience, but also directly impact the bottom line. Think about companies running mobile advertising networks that are paid for delivering an advertising impression to users swiping away at their mobile phones to flip to the next screen. If the ad doesn’t load, well, that equals lost revenue. For these customers, response time is mission-critical. A common solution for applications that require fast response times is to run the database in memory, also known as an in-memory database (IMDB). You can easily do so in the cloud; however, selecting the appropriate infrastructure and even the appropriate provider can be tricky. Depending on the provider, for example, there may be hidden charges, less-than-ideal network topologies, and in many cases, a poor selection of virtual machines.

So how do you choose a reliable provider? And do you know what you’re looking for in terms of infrastructure? There are 3 key requirements that will help you get started:

There’s no doubt that Big Data and cloud computing have the ability to transform the way we look at our jobs, our social habits, and each other. If recent research is any indication, this trend will continue as the technology begins to weave into the way the next generation is educated. Examples of data-based applications and concepts range from students learning how to read to their college graduation are growing more significant every day and promise to exert an even greater influence in the years to come.

Big Data stands to change the way the next generation learns about the world.

Emerging uses of the cloud in education
According to a recent piece from Wall Street Journal contributor Lisa Fleisher, Big Data doesn’t just track how quickly a student is learning and his or her deficiency patterns, but can also direct teachers and publishers toward more effective systems. One of the shining examples of this increasingly common practice is the “Teach to One” program underway in New York City public schools that uses digital data to track how well students are learning math concepts.

“The amount of data collected is expected to swell as more schools use apps and tablets that can collect information down to individual keystrokes, or even how long a student holds a mouse pointer above a certain answer,” the source explained.

The program is also testing effective learning environments for students. Of the data collected, each user is tested in the typical classroom, after a one-to-one teaching session, and after taking a lesson online to determine which setting is best for cognitive development. With data now available on millions of students across the country, there is more insight than ever into what works (or doesn’t work) for today’s students.

Another productive use of cloud hosting that has emerged recently is the crowd-funded Reading Rainbow application, which garnered over $5 million on the Kickstarter platform this past spring. Based on the long-running PBS television series starring LeVar Burton, the app provides reading and teaching resources aimed at children just beginning to read at a low price for elementary schools that struggle with program budgets. Although the software is still in development, the Reading Rainbow educational platform will be deployed primarily on tablets for students and on larger displays for teachers in lieu of a chalkboard.

America’s favorite pastime has always been a highly analytical sport, something that technological advancement has only done more to ingratiate into our culture. It seems perfect, then, that Big Data is gaining an important foothold among baseball fans across the country, and its involvement in the statistical side of the game only seems likely to increase in importance in the coming years. Let’s take a look at some of the ways the cloud computing phenomenon is affecting life on the diamond and the people watching at home on the sofa.

America’s favorite pastime has always been a highly analytical sport.

Big Data on the field
Like many other methods used to collect marketing information on those interested in a particular sector, baseball venues are able to learn what matters to their customers by offering something in return. According to Samantha Meckler of Smart Data Collective, this goal is accomplished by offering fans tweeting and texting from the stands free on-site Wi-Fi, giving the stadium access to their analytic data to create future advertising decisions based on this information.

“Fans now have the ability to connect at various high-speed access points throughout these spaces,” Meckler reminded readers. “This, at the very least, helps improve phone signal strength and reduce individual data charges. For teams, this provides a gateway for collecting new insights on fan behavior that contribute to an overall data-driven strategy for customer relations.”

When baseball aficionados interact with each other and post their stadium selfies to the cloud infrastructure, this also serves a dual purpose. Any flattering, exciting social media interaction with the brand is free advertising to an entire network of people who may have forgotten the season had started or wanted to buy tickets. This is part of marketing the game experience as the new “cool,” and one’s friends and family have the power to influence that outcome more than an ad on the side of a Facebook feed ever could.

Big Data off the field
Naturally, cloud computing technology has had an equally major influence on the world of sports statistics – the sheer ability to store larger amounts of information to analyze has enabled stats addicts to take their hobby even further and sports reporters to rev their engines.